How does AI apply to the language industry? AI has always been a constant question mark in the back of our minds especially regarding automatic translations. Now that AI can do so much, is it time for translators to become worried?

Today, translators use machine translation programs such as Trados or MemoQ to give them a baseline to work from, so called post-editing machine translation (PEMT). PEMT can greatly improve translation times especially for longer translations. For translators, it has been recognized as a valid strategy and working method. However as we all know, the translations that machine translation programs produce aren’t perfect. They are often more than not flawed. But what happens if you begin using AI such as Chat GPT which is designed to produce fluent and natural sounding language? Would a translator have a more powerful tool? Or would you have a competitor?

Translators will find that the answer is the same as it always has, ever since machine translation was introduced into the world. A machine will most certainly not remove the need for a translator. Language is always so fluid, full of nuance and possibilities that it’s almost impossible for a machine to pick up on every last detail. On the flip side though, translators may find a new ally with AI as it can cut their work time, allowing them to work on more projects. For example, translators can enter questions into Chat GPT, maybe have it check for fluency or suggest different ways of phrasing things, or even come up with new ideas.

If you’re an interpreter, you probably have even less to worry about. Though AIs such as Google Assistant are popular for quick and easy phrases, it still runs into the same problems as it is pulling from Google Translate. Interpretation especially is a field where accuracy and nuance is important and a lot of that is easily lost with AI translations.

Overall, in the language field, whether the advancement of AI would replace the role of human translators and interpreters is nothing to be concerned about, at least not in our life time. If anything, we should be excited about it. As the technology advances, translators and interpreters may find a powerful ally that will help them advance their work efficiently.

How the neural network works and defines the inputted numbers to produce an output is perfected by training the network with millions of sentence pairs. So for example, if you are trying to train a Neural Machine Translation engine for English to Spanish, you would need to feed the engine a great deal of data to help tweak and refine its framework and make it more accurate. Each sentence pair that is given to the engine slightly modifies the neural network while it uses an algorithm called back-propagation. Back-propagation consists of fine-tuning the error rate that comes from the previous iteration. By properly tuning, the error rates can be reduced and the accuracy can be improved.

So what is the advantage of using Neural Machine Translation? Some of the biggest limitations of other machine translation is that they have difficulty when it comes to more complex or nuanced phrases. However, with Neural Machine Translation, it becomes much more possible to translate these kinds of phrases since the number of parameters and rules that can be given provided are much greater and therefore it is more possible to generate translations that are much more natural sounding and closer in meaning.

Neural Machine Translation is without doubt the future of Machine Translation, but there are still reasons as to why it is not widely being adopted. The biggest reason is the sheer cost and time sink that the engines require to actually become useful. As mentioned earlier, millions of sentences need to be entered into the engine for it to start to really output translations that can be considered good quality, and that means using more manpower and time. Not every company is able or willing to invest that many resources to develop a Neural Machine Translation engine, and that is perfectly understandable when weighing the cost versus the reward.

Overall, Neural Machine Translation is a complicated system, but has the most potential out of all of the Machine Translation methods. It is very possible that Neural Machine Translation will be developed to the point where it can accurately be used in a variety of situations for which it is specifically trained, but it is unknown when exactly that might happen. There have been many advancements in its development, but due to its cost and time consumption it will be quite some time before it will be able to be commonly used.